Foreign Investment and the Privatization of Coercion: A Case Study of the Forza Security Company in Peru
Bibliographic record
Abstract
The Spanish version of this paper can be found at http://ssrn.com/abstract=1879915This paper explores the reorganization of security and coercive power in Peru in response to the needs of foreign owned mining companies in an environment of social protest and opposition. It begins with an analytical description of the domestic legal regime that structures security services in Peru. In this context, it undertakes a case study of Forza, one of Peru’s oldest and most powerful private security companies, recently purchased by a transnational security company. Forza’s human rights record is explored through the trajectory of three on-going human rights cases. These cases signal a deep interpenetration of the economic and political power of foreign-owned mining companies, Forza and the Peruvian justice system. The paper then analyzes the Forza case study in terms of the applicable systems of law. At the level of domestic law, the Peruvian system and the investors’ home state legal systems are considered. At the international level, three distinct normative systems are reviewed: public international human rights law, private international foreign investment law, and corporate social responsibility mechanisms. This overview provides some insight into how the “global gap” in the enforcement of domestic law and the asymmetry in the enforcement of international law function together to produce the conditions of impunity in the Forza case study. Using the case study itself as an example, this paper concludes by proposing a methodological approach to international lawyering and legal academic work in relation to social movements.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".